
from .integrations import (
    is_optuna_available,
    is_ray_available,
    is_sigopt_available,
    is_wandb_available,
    run_hp_search_optuna,
    run_hp_search_ray,
    run_hp_search_sigopt,
    run_hp_search_wandb,
)
from .trainer_utils import (
    HPSearchBackend,
    default_hp_space_optuna,
    default_hp_space_ray,
    default_hp_space_sigopt,
    default_hp_space_wandb,
)
from .utils import logging


UpperCAmelCase       =					logging.get_logger(__name__)







class 			A_  :




	'''simple docstring'''


	_UpperCamelCase	:	str
	_UpperCamelCase	:	str									=			None





	@staticmethod
	def       SCREAMING_SNAKE_CASE__		(			):
		raise NotImplementedError





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case						,       snake_case						,       **snake_case			):
		raise NotImplementedError





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		raise NotImplementedError





	def       SCREAMING_SNAKE_CASE__		(			self			):
		if not self.is_available():
			raise RuntimeError(
			    F'''You picked the {self.name} backend, but it is not installed. Run {self.pip_install()}.'''			)





	@classmethod
	def       SCREAMING_SNAKE_CASE__		(			cls			):
		return F'''`pip install {cls.pip_package or cls.name}`'''







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	_UpperCamelCase	:	Dict									=			"""optuna"""





	@staticmethod
	def       SCREAMING_SNAKE_CASE__		(			):
		return is_optuna_available()





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case						,       snake_case						,       **snake_case			):
		return run_hp_search_optuna(snake_case						,       snake_case						,       snake_case						,       **snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return default_hp_space_optuna(snake_case			)







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	_UpperCamelCase	:	Dict									=			"""ray"""
	_UpperCamelCase	:	Optional[Any]									=			"""'ray[tune]'"""





	@staticmethod
	def       SCREAMING_SNAKE_CASE__		(			):
		return is_ray_available()





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case						,       snake_case						,       **snake_case			):
		return run_hp_search_ray(snake_case						,       snake_case						,       snake_case						,       **snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return default_hp_space_ray(snake_case			)







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	_UpperCamelCase	:	Dict									=			"""sigopt"""





	@staticmethod
	def       SCREAMING_SNAKE_CASE__		(			):
		return is_sigopt_available()





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case						,       snake_case						,       **snake_case			):
		return run_hp_search_sigopt(snake_case						,       snake_case						,       snake_case						,       **snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return default_hp_space_sigopt(snake_case			)







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	_UpperCamelCase	:	List[str]									=			"""wandb"""





	@staticmethod
	def       SCREAMING_SNAKE_CASE__		(			):
		return is_wandb_available()





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case						,       snake_case						,       **snake_case			):
		return run_hp_search_wandb(snake_case						,       snake_case						,       snake_case						,       **snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return default_hp_space_wandb(snake_case			)




UpperCAmelCase       =					{
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}






def 				UpperCAmelCase_						(				):
	lowercase	    =       [backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
	if len(__SCREAMING_SNAKE_CASE				) > 0:
		lowercase	    =       available_backends[0].name
		if len(__SCREAMING_SNAKE_CASE				) > 1:
			logger.info(
			    F'''{len(__SCREAMING_SNAKE_CASE				)} hyperparameter search backends available. Using {name} as the default.'''				)
		return name
	raise RuntimeError(
	    'No hyperparameter search backend available.\n'
	    + '\n'.join(
	        F''' - To install {backend.name} run {backend.pip_install()}'''
	        for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values()				)				)






'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase:   List[Any]					=		{'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConfig']}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   Dict					=		['ReformerTokenizer']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   Tuple					=		['ReformerTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   List[Any]					=		[
         'REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'ReformerAttention',
         'ReformerForMaskedLM',
         'ReformerForQuestionAnswering',
         'ReformerForSequenceClassification',
         'ReformerLayer',
         'ReformerModel',
         'ReformerModelWithLMHead',
         'ReformerPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_reformer import ReformerTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_reformer_fast import ReformerTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_reformer import (
              REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              ReformerAttention,
              ReformerForMaskedLM,
              ReformerForQuestionAnswering,
              ReformerForSequenceClassification,
              ReformerLayer,
              ReformerModel,
              ReformerModelWithLMHead,
              ReformerPreTrainedModel,
          )

else:
     import sys

     lowerCAmelCase:   str					=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)